Cody Hyndman, PhD
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- Full Professor, Mathematics and Statistics
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Supervised programs: Mathematics and Statistics (MA, MSc), Mathematics and Statistics (PhD)
Research areas: Mathematical Finance, Computational Finance, Probability and Stochastic Analysis, Filtering and Control, Statistics, Insurance Mathematics, Machine Learning
Contact information
Email:
Website:
Biography
Education
Ph.D.: University of Waterloo, Canada 2005
Positions
06/2023-present: (Full) Professor
07/2017-06/2023: Department Chair (Academic Unit Head)
06/2011-05/2023: Associate Professor
07/2006-05/2011: Assistant Professor
Awards
06/2023: Concordia Academic Leadership Award
Teaching activities
Recent Courses
STAT 385: Neural Networks
MACF 401: Mathematical and Computational Finance I
MACF 402: Mathematical and Computational Finance II
Research activities
Recent Publications
Kratsios, A, Hyndman, C. Generative Ornstein Uhlenbeck Markets via Geometric Deep Learning. In: Nielsen, F., Barbaresco, F. (eds) Geometric Science of Information. GSI 2023. Lecture Notes in Computer Science, vol 14072. Springer, Cham. 2023; Part II: 605-614.
Kratsios A, Hyndman C. NEU: A Meta-Algorithm for Universal UAP-Invariant Feature Representation. Journal of Machine Learning Research. 2021; 22(92): 1-51.
Kratsios A, Hyndman C. Deep Arbitrage-free Learning in a Generalized HJM Framework via Arbitrage-Regularization. Risks. 2020; 8(2), 40: 1-30.
Wang R, Hyndman C, Kratsios A. The Entropic Measure Transform. The Canadian Journal of Statistics. 2020; 48(1): 97-129.
Hillairet C, Hyndman C, Jiao Y, Wang, R. Trading against disorderly liquidation of a large position under asymmetric information and market impact. ESAIM: Proceedings and Surveys. 2017; 56: 42-71.
Hyndman C, Oyono Ngou P. A Convolution Method for Numerical Solution of Backward Stochastic Differential Equations. Methodology and Computing in Applied Probability. 2017; 19(1): 1-29.
Publications
A full list of my publications and preprints is available on this webpage:
http://mypage.concordia.ca/alcor/chyndman/research.html
Funding
Research and Funding Opportunities for Students
Co-founder of the NSERC CREATE Program on Machine Learning in Quantitative Finance and Business Analytics (FIN-ML).
Students (graduate and undergraduate) pursuing a degree in the Department of Mathematics and Statistics under my supervision may apply for FIN-ML scholarships and participate in the training program, research, and industrial internships.
Research Grants (Current)
NSERC Discovery
MITACS Accelerate
NSERC Create